Feasibility of in vivo multi-parametric quantitative magnetic resonance imaging of the healthy sciatic nerve with a unified signal readout protocol

Magnetic resonance neurography (MRN) has been used successfully over the years to investigate the peripheral nervous system (PNS) because it allows early detection and precise localisation of neural tissue damage. However, studies demonstrating the feasibility of combining MRN with multi-parametric quantitative magnetic resonance imaging (qMRI) methods, which provide more specific information related to nerve tissue composition and microstructural organisation, can be invaluable. The translation of emerging qMRI methods previously validated in the central nervous system to the PNS offers real potential to characterise in patients in vivo the underlying pathophysiological mechanisms involved in a plethora of conditions of the PNS. The aim of this study was to assess the feasibility of combining MRN with qMRI to measure diffusion, magnetisation transfer and relaxation properties of the healthy sciatic nerve in vivo using a unified signal readout protocol. The reproducibility of the multi-parametric qMRI protocol as well as normative qMRI measures in the healthy sciatic nerve are reported. The findings presented herein pave the way to the practical implementation of joint MRN-qMRI in future studies of pathological conditions affecting the PNS.

Pre-processing of qMRI data. All acquired qMRI volumes (i.e., DWI, qMT, IR) were pre-processed collectively using a previously reported denoising approach for dealing with multi-parametric data obtained with unified signal readout, and where the benefits of denoising were demonstrated specifically using a similar acquisition scheme 45 . The diffusion-weighted images were additionally motion corrected using slice-wise linear registration implemented in FSL (http:// www. fmrib. ox. ac. uk/ fsl), with registration transformations estimated among non-DWI images (i.e., b = 0), interleaved throughout the diffusion acquisition scheme as previously described 48 .
• The DWI signals were fitted to the acquired multi-shell DW data using the DiPy Dkifit command (https:// dipy. org/ docum entat ion/1. 0. 0./ examp les_ built/ recon st_ dki/) 49,50 ; from the fitting, standard DTI metrics were obtained, namely AD, RD, MD, FA, and also metrics derived from DKI 41 , namely AK, RK and MK. • qMT data were analysed using a simplified two-pool model, as previously described 51 , to obtain estimates of BPF and T2 B . • Quantitative longitudinal relaxation time (qT1) maps were obtained from the IR data, by fitting a monoexponential recovery model as previously described 47 .  In the healthy sciatic nerve, the main biological compartments underlying the qMRI metrics are myelin, intra-axonal water (in both myelinated and unmyelinated axons) and extra-axonal space (endoneurium). However, metrics can also be influenced by surrounding tissue compartments (e.g., perineurium, lipid equivalent connective tissue). Note: Although qT1 is known to be sensitive to myelin, the overall macroscopic T1 is rather unspecific, and is likely to be influenced by almost all biological compartments shown (e.g., myelin, amount of intra-and extraaxonal water, as well as potential exchange between the two water populations).

Scientific Reports
| (2023) 13:6565 | https://doi.org/10.1038/s41598-023-33618-w www.nature.com/scientificreports/ Reproducibility assessment. In order to assess scan-rescan reproducibility, six of the twelve subjects underwent a second scan on a separate visit (between 2 and 4 weeks from the first visit). In order to evaluate intra-rater reproducibility, the same rater (RB) segmented the images from the first visit of six participants twice on separate occasions, waiting at least two weeks between analyses. To examine inter-rater reproducibility, the data from the first visit of the six participants were analysed by a second rater (MY), with both raters working independently from one another. Then the scan-rescan reproducibility was assessed by a single rater (RB) conducting image segmentation on the data from the first and second visits.
Statistical analysis. The mean and standard deviation (± SD) of all qMRI metrics across all study participants were calculated to report normative values in the sciatic nerve. In order to evaluate scan-rescan, intra-and inter-rater reproducibility, the percent coefficient of variation (%COV) was calculated using the mean and standard deviation from the repeated measures and the following equation: COV = [SD/mean] × 100%. Moreover, the intra-rater and inter-rater reproducibility were assessed using the intraclass correlation coefficient (ICC) 52 , which can be used to estimate the measurement error relative to the biological variability between subjects. In order to assess the intra-and inter-rater quality of the segmentations, the Dice similarity coefficient was calculated (DSC) 53 . The DSC is a measurement between two data sets calculated by dividing the size of the union of the two sets by the mean size of the two sets. The DSC range is from 0 to 1, where 0 implies no spatial overlap between two sets of binary segmentation masks and 1 represents total overlap.

Results
Data from all 12 healthy volunteers, including data from repeated scanning in 6 healthy volunteers, were processed successfully without having to discard any because of motion-related artifacts. Figure 3 shows example maps of the standard DTI metrics (AD/RD/MD/FA), DKI metrics (AK/RK/MK), qMT (BPF/T2 B ) and IR (qT1) in a single healthy control. Table 1 shows the mean (± SD) values of all qMRI metrics calculated in all study participants (N = 12), with the corresponding boxplots of all metrics shown in Fig. 4.
Reproducibility assessment. Table 2 shows the %COV results of the scan-rescan, intra-rater and interrater reproducibility assessments for each qMRI metric separately. In terms of scan-rescan reproducibility, all metrics had a COV value lower than 9% except for BPF, RK and T2 B (13.2%, 15.9% and 20.9%, respectively). In terms of the intra-rater results, all metrics had a COV value lower than 6%. Inter-rater results were similar to the intra-rater results, except for RK (10.6%). Table 3 shows the results of the intra-rater and inter-rater reproducibility assessments, expressed as the ICC. In terms of the intra-rater reproducibility, all metrics had ICC values higher than 0.86 (range 0.86-0.99). In terms of inter-rater reproducibility, all metrics had ICC values higher than  Table 4 shows the DSC results of the intra-rater and inter-rater assessments of image segmentation quality, with intra-rater mean (± SD) DSC of 0.69 (0.06) and inter-rater of 0.72 (0.07).

Discussion
In this pilot study, the feasibility of using advanced qMRI methods in conjunction with MRN in the PNS was investigated, with application to the sciatic nerve in healthy volunteers. The rationale for this study was based on the limited number of prospective in vivo studies employing advanced qMRI methods to study the PNS, despite their demonstrated ability to provide biophysically meaningful information pertinent to the underlying pathophysiological mechanisms involved in neurological disease 6 . The main reasons behind the limited implementation of qMRI methods in this context are likely to be related to the technical challenges associated with imaging the peripheral nerves, which include among others the small structure of the peripheral nerves, the surrounding tissue types with different magnetic susceptibility properties, the blood vessel distribution and flow effects, and RF coil and pulse sequence designs. www.nature.com/scientificreports/ In this study, the reproducibility and reliability of a multi-parametric qMRI protocol was investigated by taking into account the main technical challenges involved to perform multi-shell DWI (for the estimation of DTI and DKI metrics), qMT (for the estimation of BPF and T2 B ) and IR (for the estimation of qT1) on a commercial 3T MRI system. A key feature of the qMRI protocol in this study included the use of ZOOM EPI, which benefits from the combined use of fat saturation with inner volume excitation, allowing alias free images with reduced Table 2. Percent coefficient of variation (%COV) results of the standard DTI metrics axial/radial/mean diffusivity (AD/RD/MD) and fractional anisotropy (FA), DKI metrics axial/radial/mean kurtosis (AK/RK/ MK), quantitative magnetisation transfer (qMT) metrics bound pool fraction and bound pool transverse relaxation time (BPF/T2 B ) and quantitative longitudinal relaxation time (qT1), for scan-rescan, intra-rater and inter-rater reproducibility assessments in 6 healthy volunteers.  Table 3. Intraclass correlation coefficient (ICC) results of the standard DTI metrics axial/radial/mean diffusivity (AD/RD/MD) and fractional anisotropy (FA), DKI metrics axial/radial/mean kurtosis (AK/RK/ MK), quantitative magnetisation transfer (qMT) metrics bound pool fraction and bound pool transverse relaxation time (BPF/T2 B ) and quantitative longitudinal relaxation time (qT1), for intra-rater and inter-rater reproducibility assessments in 6 healthy volunteers. www.nature.com/scientificreports/ sensitivity to the susceptibility artifacts that commonly affect long EPI readout acquisitions 43,44 . In addition, the qMRI protocol was acquired with a unified MRI signal readout, which enabled the acquisition of a uniquely rich set of image contrasts with matched resolution, distortion and intrinsic geometric alignment, all important aspects for successful multimodal characterisation of neural tissue microstructure 45 . Indeed, our unified-ZOOM EPI acquisition strategy is one of the main innovations of this work. The strategy makes high-quality multiparametric qMRI feasible in the PNS, and has the potential of bringing advanced MRI methods for quantitative microstructural assessment one step closer to the clinic. Without the use of ZOOM-EPI for all our qMRI metrics, taking advantage of acceleration methods such as multi-slice excitation and parallel imaging reconstruction, this protocol would be much longer, and as a consequence a reduced choice of metrics would be sampled. Previous studies have used DWI to examine the median, ulnar, radial, tibial and sciatic nerves, demonstrating the reliability of these measurements 9 , and how these maybe influenced by the anatomical location, age, sex, height, weight, body mass index (BMI) 10,11 , and by the nature of the pathological conditions implicating the PNS [12][13][14][15][16] . These studies have focussed on conventional DTI metrics (i.e., MD, RD, AD and FA), thus providing more specific information related to axon and myelin sheath integrity, typically invisible with conventional structural imaging.

Intra-rater
This study sought to examine the feasibility of extending such previous approaches focussing on conventional DTI metrics by accounting for non-Gaussian diffusion through DKI 18 , in order to obtain additional information related to neural tissue microstructure. However, the additional information likely to be obtained through the use of DKI in the peripheral nerves may not be straightforward to interpret, given differences in tissue composition and microstructural organisation, as compared to the CNS. For example, differences in magnetic susceptibility properties between tissue types have also been shown to influence DKI metrics in the CNS 54 , and for this reason, similar investigations in the PNS are warranted to understand the possible source of image contrast in DKI. In terms of the standard DTI metrics, the mean values obtained in this study seem to follow a similar trend and appear to be in agreement with the results of previous studies examining the sciatic nerve in healthy controls 9,11 , although differences in technical and demographic factors do not permit a direct comparison. The potential value and feasibility of DKI measurements in the PNS has previously been explored in animal models 55 , but has only recently been addressed in vivo 56 . Therefore, more studies will be required in the future to understand the additional information related to tissue composition and microstructure that can potentially be obtained in pathological conditions affecting the PNS.
The role of qMT in the study of the PNS currently remains unexplored, despite the potential benefits previously demonstrated [32][33][34][35][36][37] , with most of the studies in the PNS currently relying on semi-quantitative assessments of myelin content through the use of MTR [24][25][26][27][28] . Future studies will therefore aim to clarify the potential benefits of using qMT in the PNS over semi-quantitative approaches like MTR. However, similar to MTR measurements, it is important to recognise the differences in tissue structure and composition of the nerves in the PNS as compared to the CNS, in order to interpret the origin of the qMT contrast in future investigations of pathological conditions affecting the PNS. In particular, assuming a two-pool description of biological tissues, the bound pool fraction in the PNS is represented by various tissue types, such as collagen, myelin and the proteins contained in the axons and Schwan cells 24,26 , thus dissimilar to the CNS tissue composition. The relative contribution of each tissue type to the qMT measurements remains unknown, and future research will be directed at addressing this gap.
The measurement of T1 relaxation time has provided invaluable information in a variety of clinical applications over the years 38 , although the limited implementation of T1 relaxometry in the study of the PNS is likely explained by the technical challenges associated with obtaining accurate T1 measurements 41 . Despite the availability of a variety of time-efficient T1 mapping methods to study the CNS 57-60 , their translation to the PNS may not be straightforward, and could be hampered by a number of site-specific factors such as radiofrequency pulse imperfections and incomplete magnetisation spoiling 41 . In this study, an IR-based T1 mapping method was used, benefiting from the aforementioned inherent qualities of ZOOM EPI acquisitions 43,44 , while making use of a slice shuffling scheme to allow T1 mapping of a large section of the sciatic nerve in a clinically acceptable scan time 47 . The mean T1 relaxation time in the healthy sciatic nerve was found to be longer (1635 ms) than previously measured in the healthy cervical spinal cord (1142 ms) using the same approach 47 , and also slightly longer than the previously reported T1 relaxation time in the healthy median nerve (1410 ms) at 3 T, using a different T1 mapping approach 61 . As previously mentioned, these variations might be explained by technical factors, anatomical location i.e., differences in tissue organisation and properties, and also demographic factors. More research will be required in the future to determine the role of T1 relaxometry in the study of the PNS.
In this study, reproducibility of the qMRI measurements was assessed by means of calculating the scan-rescan, intra-rater and inter-rater %COV from repeated measurements in a subset of study participants. Furthermore, intra-rater and inter-rater reproducibility was assessed by means of calculating the ICC. In order to assess the intra-rater and inter-rater quality of the image segmentations, the DSC was also calculated. Similar studies in the literature utilising a multi-parametric qMRI protocol with which to directly compare the reproducibility results of this study are not available. When comparing the %COV values obtained in this study with previous similar investigations in the brain and spinal cord, however, one must take into consideration the smaller size of the structure evaluated in this study. In particular, partial volume averaging is expected to have higher influence when assessing smaller structures, which is also supported by the moderate intra-rater and inter-rater DSC results in this study. Nevertheless, the ICC results of this study for the standard DTI metrics have demonstrated good to excellent agreement 62 , and are in line with previous similar investigations in the sciatic nerve 9 .
Finally, we acknowledge a number of limitations of our approach. One of main limitations of this study is that with 12 subjects the effect of age, gender, BMI, height and weight on the multi-parametric qMRI measurements obtained in this pilot study was not examined specifically, even though some of the demographic factors have been shown to influence various qMRI measurements significantly 11 . In addition, some of the unique technical features employed in this study, for example the use of ZOOM EPI, together with modifications to the Scientific Reports | (2023) 13:6565 | https://doi.org/10.1038/s41598-023-33618-w www.nature.com/scientificreports/ sequence design in order to allow time-efficient acquisition of the qMRI metrics reported herein, may not be readily available in non-specialist centres, thus limiting the widespread implementation of the proposed qMRI protocol. Also, while DTI fitting is now part of most scanner software packages, analysis of advanced features such as DKI, qMT and qT1 are bespoke for our protocol.
In conclusion, this pilot study demonstrates the feasibility of combining MRN with a rich multi-parametric qMRI protocol based on a unified ZOOM-EPI readout, which enables the measurement of diffusion, quantitative magnetisation transfer and T1 relaxation properties of the healthy sciatic nerve in vivo. The reproducibility of the qMRI methods employed were found to be consistent with previous studies, demonstrated by the comparably low %COV, high ICC and DSC values obtained from scan-rescan sessions, intra-rater and inter-rater assessments. Future investigations involving a larger sample population will be required to confirm the findings of this study, to explore the demographic determinants of the qMRI measurements investigated, and to determine their potential role in pathological conditions implicating the PNS.

Data availability
The datasets used and analysed during the current study, as well as the code employed for the pre-processing and processing of the qMRI data, can be made available by the corresponding author on reasonable request.